Publisher
Springer Science and Business Media LLC
Subject
Artificial Intelligence,Computer Networks and Communications,Computer Vision and Pattern Recognition,Human-Computer Interaction,Software
Reference71 articles.
1. Raissi, M., Perdikaris, P. & Karniadakis, G. E. Machine learning of linear differential equations using Gaussian processes. J. Comput. Phys. 348, 683–693 (2017).
2. Han, J., Jentzen, A. & Weinan, E. Solving high-dimensional partial differential equations using deep learning. Proc. Natl Acad. Sci. USA 115, 8505–8510 (2018).
3. Bar-Sinai, Y., Hoyer, S., Hickey, J. & Brenner, M. P. Learning data-driven discretizations for partial differential equations. Proc. Natl Acad. Sci. USA 116, 15344–15349 (2019).
4. Sanchez-Gonzalez, A. et al. Learning to simulate complex physics with graph networks. In International Conference on Machine Learning 8459–8468 (PMLR, 2020).
5. Long, Z., Lu, Y., Ma, X. & Dong, B. PDE-Net: learning PDEs from data. In International Conference on Machine Learning 3208–3216 (PMLR, 2018).
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28 articles.
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